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1.
Nat Commun ; 15(1): 3636, 2024 May 06.
Article in English | MEDLINE | ID: mdl-38710699

ABSTRACT

Polypharmacology drugs-compounds that inhibit multiple proteins-have many applications but are difficult to design. To address this challenge we have developed POLYGON, an approach to polypharmacology based on generative reinforcement learning. POLYGON embeds chemical space and iteratively samples it to generate new molecular structures; these are rewarded by the predicted ability to inhibit each of two protein targets and by drug-likeness and ease-of-synthesis. In binding data for >100,000 compounds, POLYGON correctly recognizes polypharmacology interactions with 82.5% accuracy. We subsequently generate de-novo compounds targeting ten pairs of proteins with documented co-dependency. Docking analysis indicates that top structures bind their two targets with low free energies and similar 3D orientations to canonical single-protein inhibitors. We synthesize 32 compounds targeting MEK1 and mTOR, with most yielding >50% reduction in each protein activity and in cell viability when dosed at 1-10 µM. These results support the potential of generative modeling for polypharmacology.


Subject(s)
Molecular Docking Simulation , Humans , TOR Serine-Threonine Kinases/metabolism , Polypharmacology , MAP Kinase Kinase 1/antagonists & inhibitors , MAP Kinase Kinase 1/metabolism , MAP Kinase Kinase 1/chemistry , Protein Kinase Inhibitors/pharmacology , Protein Kinase Inhibitors/chemistry , Protein Binding , Drug Discovery/methods , Drug Design , Cell Survival/drug effects
2.
Nature ; 600(7889): 536-542, 2021 12.
Article in English | MEDLINE | ID: mdl-34819669

ABSTRACT

The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.


Subject(s)
Chromosomes , Proteome , Antigens, Nuclear/genetics , Antigens, Nuclear/metabolism , Chromatin/genetics , Chromosomes/metabolism , Humans , Nuclear Matrix-Associated Proteins/metabolism , Proteome/metabolism , RNA, Ribosomal , RNA-Binding Proteins/genetics
3.
Science ; 374(6563): eabf3067, 2021 Oct.
Article in English | MEDLINE | ID: mdl-34591613

ABSTRACT

A major goal of cancer research is to understand how mutations distributed across diverse genes affect common cellular systems, including multiprotein complexes and assemblies. Two challenges­how to comprehensively map such systems and how to identify which are under mutational selection­have hindered this understanding. Accordingly, we created a comprehensive map of cancer protein systems integrating both new and published multi-omic interaction data at multiple scales of analysis. We then developed a unified statistical model that pinpoints 395 specific systems under mutational selection across 13 cancer types. This map, called NeST (Nested Systems in Tumors), incorporates canonical processes and notable discoveries, including a PIK3CA-actomyosin complex that inhibits phosphatidylinositol 3-kinase signaling and recurrent mutations in collagen complexes that promote tumor proliferation. These systems can be used as clinical biomarkers and implicate a total of 548 genes in cancer evolution and progression. This work shows how disparate tumor mutations converge on protein assemblies at different scales.


Subject(s)
Neoplasm Proteins/genetics , Neoplasm Proteins/metabolism , Neoplasms/genetics , Neoplasms/metabolism , Protein Interaction Maps/genetics , Genes, Neoplasm , Humans , Mutation , Protein Interaction Mapping/methods
4.
G3 (Bethesda) ; 10(9): 2981-2988, 2020 09 02.
Article in English | MEDLINE | ID: mdl-32732306

ABSTRACT

Genetic screens in Saccharomyces cerevisiae have allowed for the identification of many genes as sensors or effectors of DNA damage, typically by comparing the fitness of genetic mutants in the presence or absence of DNA-damaging treatments. However, these static screens overlook the dynamic nature of DNA damage response pathways, missing time-dependent or transient effects. Here, we examine gene dependencies in the dynamic response to ultraviolet radiation-induced DNA damage by integrating ultra-high-density arrays of 6144 diploid gene deletion mutants with high-frequency time-lapse imaging. We identify 494 ultraviolet radiation response genes which, in addition to recovering molecular pathways and protein complexes previously annotated to DNA damage repair, include components of the CCR4-NOT complex, tRNA wobble modification, autophagy, and, most unexpectedly, 153 nuclear-encoded mitochondrial genes. Notably, mitochondria-deficient strains present time-dependent insensitivity to ultraviolet radiation, posing impaired mitochondrial function as a protective factor in the ultraviolet radiation response.


Subject(s)
Saccharomyces cerevisiae Proteins , Ultraviolet Rays , DNA Damage , DNA Repair , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism
5.
Cell Syst ; 11(2): 176-185.e6, 2020 08 26.
Article in English | MEDLINE | ID: mdl-32619550

ABSTRACT

All mammals progress through similar physiological stages throughout life, from early development to puberty, aging, and death. Yet, the extent to which this conserved physiology reflects underlying genomic events is unclear. Here, we map the common methylation changes experienced by mammalian genomes as they age, focusing on comparison of humans with dogs, an emerging model of aging. Using oligo-capture sequencing, we characterize methylomes of 104 Labrador retrievers spanning a 16-year age range, achieving >150× coverage within mammalian syntenic blocks. Comparison with human methylomes reveals a nonlinear relationship that translates dog-to-human years and aligns the timing of major physiological milestones between the two species, with extension to mice. Conserved changes center on developmental gene networks, which are sufficient to translate age and the effects of anti-aging interventions across multiple mammals. These results establish methylation not only as a diagnostic age readout but also as a cross-species translator of physiological aging milestones.


Subject(s)
Aging/genetics , DNA Methylation/genetics , Animals , Dogs , Humans
6.
Methods Mol Biol ; 2049: 73-85, 2019.
Article in English | MEDLINE | ID: mdl-31602605

ABSTRACT

Systematic measurements of genetic interactions have been used to classify gene functions and to categorize genes into protein complexes, functional pathways and biological processes. This protocol describes how to perform a high-throughput genetic interaction screen in S. cerevisiae using a variant of epistatic miniarray profiles (E-MAP) in which the fitnesses of 6144 colonies are measured simultaneously. We also describe the computational methods to analyze the resulting data.


Subject(s)
Epistasis, Genetic/genetics , Genome, Fungal/genetics , Saccharomyces cerevisiae/genetics
7.
Nat Genet ; 50(4): 613-620, 2018 04.
Article in English | MEDLINE | ID: mdl-29610481

ABSTRACT

Although cancer genomes are replete with noncoding mutations, the effects of these mutations remain poorly characterized. Here we perform an integrative analysis of 930 tumor whole genomes and matched transcriptomes, identifying a network of 193 noncoding loci in which mutations disrupt target gene expression. These 'somatic eQTLs' (expression quantitative trait loci) are frequently mutated in specific cancer tissues, and the majority can be validated in an independent cohort of 3,382 tumors. Among these, we find that the effects of noncoding mutations on DAAM1, MTG2 and HYI transcription are recapitulated in multiple cancer cell lines and that increasing DAAM1 expression leads to invasive cell migration. Collectively, the noncoding loci converge on a set of core pathways, permitting a classification of tumors into pathway-based subtypes. The somatic eQTL network is disrupted in 88% of tumors, suggesting widespread impact of noncoding mutations in cancer.


Subject(s)
Genes, Neoplasm , Mutation , Neoplasms/genetics , Adaptor Proteins, Signal Transducing/genetics , Aldose-Ketose Isomerases/genetics , Cell Line, Tumor , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Humans , Microfilament Proteins , Monomeric GTP-Binding Proteins/genetics , Neoplasm Invasiveness/genetics , Neoplasms/metabolism , Quantitative Trait Loci , RNA, Messenger/genetics , RNA, Messenger/metabolism , RNA, Neoplasm/genetics , RNA, Neoplasm/metabolism , RNA, Untranslated/genetics , RNA, Untranslated/metabolism , Whole Genome Sequencing , rho GTP-Binding Proteins
8.
Mol Cancer Ther ; 17(7): 1585-1594, 2018 07.
Article in English | MEDLINE | ID: mdl-29636367

ABSTRACT

Human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) represents a distinct classification of cancer with worse expected outcomes. Of the 11 genes recurrently mutated in HNSCC, we identify a singular and substantial survival advantage for mutations in the gene encoding Nuclear Set Domain Containing Protein 1 (NSD1), a histone methyltransferase altered in approximately 10% of patients. This effect, a 55% decrease in risk of death in NSD1-mutated versus non-mutated patients, can be validated in an independent cohort. NSD1 alterations are strongly associated with widespread genome hypomethylation in the same tumors, to a degree not observed for any other mutated gene. To address whether NSD1 plays a causal role in these associations, we use CRISPR-Cas9 to disrupt NSD1 in HNSCC cell lines and find that this leads to substantial CpG hypomethylation and sensitivity to cisplatin, a standard chemotherapy in head and neck cancer, with a 40% to 50% decrease in the IC50 value. Such results are reinforced by a survey of 1,001 cancer cell lines, in which loss-of-function NSD1 mutations have an average 23% decrease in cisplatin IC50 value compared with cell lines with wild-type NSD1Significance: This study identifies a favorable subtype of HPV-negative HNSCC linked to NSD1 mutation, hypomethylation, and cisplatin sensitivity. Mol Cancer Ther; 17(7); 1585-94. ©2018 AACR.


Subject(s)
Carcinoma, Squamous Cell/drug therapy , DNA Methylation/genetics , Head and Neck Neoplasms/drug therapy , Intracellular Signaling Peptides and Proteins/genetics , Nuclear Proteins/genetics , CRISPR-Cas Systems/genetics , Carcinoma, Squamous Cell/genetics , Carcinoma, Squamous Cell/pathology , Cell Line, Tumor , Cisplatin/pharmacology , CpG Islands/drug effects , DNA Methylation/drug effects , Drug Resistance, Neoplasm/genetics , Female , Gene Expression Regulation, Neoplastic/drug effects , Head and Neck Neoplasms/genetics , Head and Neck Neoplasms/pathology , Histone Methyltransferases , Histone-Lysine N-Methyltransferase , Humans , Male , Mutation/drug effects , Papillomaviridae
9.
Nat Methods ; 14(6): 573-576, 2017 Jun.
Article in English | MEDLINE | ID: mdl-28319113

ABSTRACT

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies.


Subject(s)
Chromosome Mapping/methods , Clustered Regularly Interspaced Short Palindromic Repeats/genetics , Combinatorial Chemistry Techniques , Epistasis, Genetic/genetics , Neoplasm Proteins/genetics , A549 Cells , Cell Line, Tumor , HeLa Cells , High-Throughput Nucleotide Sequencing , Humans
10.
Mol Cell ; 65(4): 761-774.e5, 2017 Feb 16.
Article in English | MEDLINE | ID: mdl-28132844

ABSTRACT

We have developed a general progressive procedure, Active Interaction Mapping, to guide assembly of the hierarchy of functions encoding any biological system. Using this process, we assemble an ontology of functions comprising autophagy, a central recycling process implicated in numerous diseases. A first-generation model, built from existing gene networks in Saccharomyces, captures most known autophagy components in broad relation to vesicle transport, cell cycle, and stress response. Systematic analysis identifies synthetic-lethal interactions as most informative for further experiments; consequently, we saturate the model with 156,364 such measurements across autophagy-activating conditions. These targeted interactions provide more information about autophagy than all previous datasets, producing a second-generation ontology of 220 functions. Approximately half are previously unknown; we confirm roles for Gyp1 at the phagophore-assembly site, Atg24 in cargo engulfment, Atg26 in cytoplasm-to-vacuole targeting, and Ssd1, Did4, and others in selective and non-selective autophagy. The procedure and autophagy hierarchy are at http://atgo.ucsd.edu/.


Subject(s)
Autophagy/genetics , Gene Regulatory Networks , Genomics/methods , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae/genetics , Systems Biology/methods , Autophagy-Related Proteins/genetics , Autophagy-Related Proteins/metabolism , Databases, Genetic , Endosomal Sorting Complexes Required for Transport/genetics , Endosomal Sorting Complexes Required for Transport/metabolism , GTPase-Activating Proteins/genetics , GTPase-Activating Proteins/metabolism , Gene Expression Regulation, Fungal , Glucosyltransferases/genetics , Glucosyltransferases/metabolism , Humans , Models, Genetic , Pichia/genetics , Pichia/metabolism , Protein Interaction Maps , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Systems Integration
11.
Mol Cell ; 63(3): 514-25, 2016 08 04.
Article in English | MEDLINE | ID: mdl-27453043

ABSTRACT

An emerging therapeutic strategy for cancer is to induce selective lethality in a tumor by exploiting interactions between its driving mutations and specific drug targets. Here we use a multi-species approach to develop a resource of synthetic lethal interactions relevant to cancer therapy. First, we screen in yeast ∼169,000 potential interactions among orthologs of human tumor suppressor genes (TSG) and genes encoding drug targets across multiple genotoxic environments. Guided by the strongest signal, we evaluate thousands of TSG-drug combinations in HeLa cells, resulting in networks of conserved synthetic lethal interactions. Analysis of these networks reveals that interaction stability across environments and shared gene function increase the likelihood of observing an interaction in human cancer cells. Using these rules, we prioritize ∼10(5) human TSG-drug combinations for future follow-up. We validate interactions based on cell and/or patient survival, including topoisomerases with RAD17 and checkpoint kinases with BLM.


Subject(s)
Antineoplastic Agents/therapeutic use , Biomarkers, Tumor/genetics , Gene Regulatory Networks/drug effects , Genes, Tumor Suppressor , Mutation , Precision Medicine/methods , Protein Interaction Maps/drug effects , Saccharomyces cerevisiae/drug effects , Uterine Cervical Neoplasms/drug therapy , Cell Cycle Proteins/genetics , Cell Cycle Proteins/metabolism , Cell Proliferation/drug effects , Cell Survival/drug effects , Dose-Response Relationship, Drug , Female , Gene Expression Regulation, Fungal/drug effects , Gene Expression Regulation, Neoplastic/drug effects , Genetic Predisposition to Disease , HeLa Cells , Humans , Kaplan-Meier Estimate , Molecular Targeted Therapy , Phenotype , RNA Interference , RecQ Helicases/genetics , RecQ Helicases/metabolism , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism , Signal Transduction/drug effects , Synthetic Lethal Mutations , Time Factors , Transfection , Uterine Cervical Neoplasms/genetics , Uterine Cervical Neoplasms/metabolism , Uterine Cervical Neoplasms/mortality
12.
Mol Cell ; 62(2): 157-168, 2016 04 21.
Article in English | MEDLINE | ID: mdl-27105112

ABSTRACT

HIV-infected individuals are living longer on antiretroviral therapy, but many patients display signs that in some ways resemble premature aging. To investigate and quantify the impact of chronic HIV infection on aging, we report a global analysis of the whole-blood DNA methylomes of 137 HIV+ individuals under sustained therapy along with 44 matched HIV- individuals. First, we develop and validate epigenetic models of aging that are independent of blood cell composition. Using these models, we find that both chronic and recent HIV infection lead to an average aging advancement of 4.9 years, increasing expected mortality risk by 19%. In addition, sustained infection results in global deregulation of the methylome across >80,000 CpGs and specific hypomethylation of the region encoding the human leukocyte antigen locus (HLA). We find that decreased HLA methylation is predictive of lower CD4 / CD8 T cell ratio, linking molecular aging, epigenetic regulation, and disease progression.


Subject(s)
Aging/genetics , DNA Methylation , Epigenesis, Genetic , HIV Infections/genetics , HLA Antigens/genetics , Aging/immunology , Anti-HIV Agents/therapeutic use , CD4-CD8 Ratio , Case-Control Studies , Chronic Disease , CpG Islands , Disease Progression , Gene Expression Profiling , Genome-Wide Association Study , Genotype , HIV Infections/diagnosis , HIV Infections/drug therapy , HIV Infections/immunology , HIV Infections/mortality , HLA Antigens/immunology , Humans , Models, Genetic , Phenotype , Risk Factors , Time Factors , Treatment Outcome
13.
Cell Syst ; 2(2): 77-88, 2016 Feb 24.
Article in English | MEDLINE | ID: mdl-26949740

ABSTRACT

Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.

14.
Oncotarget ; 6(34): 35755-69, 2015 Nov 03.
Article in English | MEDLINE | ID: mdl-26437225

ABSTRACT

Chemical inhibitors of the checkpoint kinases have shown promise in the treatment of cancer, yet their clinical utility may be limited by a lack of molecular biomarkers to identify specific patients most likely to respond to therapy. To this end, we screened 112 known tumor suppressor genes for synthetic lethal interactions with inhibitors of the CHEK1 and CHEK2 checkpoint kinases. We identified eight interactions, including the Replication Factor C (RFC)-related protein RAD17. Clonogenic assays in RAD17 knockdown cell lines identified a substantial shift in sensitivity to checkpoint kinase inhibition (3.5-fold) as compared to RAD17 wild-type. Additional evidence for this interaction was found in a large-scale functional shRNA screen of over 100 genotyped cancer cell lines, in which CHEK1/2 mutant cell lines were unexpectedly sensitive to RAD17 knockdown. This interaction was widely conserved, as we found that RAD17 interacts strongly with checkpoint kinases in the budding yeast Saccharomyces cerevisiae. In the setting of RAD17 knockdown, CHEK1/2 inhibition was found to be synergistic with inhibition of WEE1, another pharmacologically relevant checkpoint kinase. Accumulation of the DNA damage marker γH2AX following chemical inhibition or transient knockdown of CHEK1, CHEK2 or WEE1 was magnified by knockdown of RAD17. Taken together, our data suggest that CHEK1 or WEE1 inhibitors are likely to have greater clinical efficacy in tumors with RAD17 loss-of-function.


Subject(s)
Antineoplastic Agents/pharmacology , Cell Cycle Proteins/metabolism , DNA-Binding Proteins/metabolism , Neoplasms/drug therapy , Nuclear Proteins/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/physiology , Saccharomyces cerevisiae/pathogenicity , Thiophenes/pharmacology , Urea/analogs & derivatives , Biomarkers, Pharmacological/metabolism , Cell Cycle/drug effects , Cell Cycle/genetics , Cell Cycle Proteins/genetics , Checkpoint Kinase 1 , Checkpoint Kinase 2/genetics , Checkpoint Kinase 2/metabolism , DNA Damage/drug effects , DNA Damage/genetics , DNA-Binding Proteins/genetics , Drug Discovery , HeLa Cells , Humans , Molecular Targeted Therapy , Mutation/genetics , Neoplasms/diagnosis , Nuclear Proteins/genetics , Protein Kinases/genetics , Protein Kinases/metabolism , Protein-Tyrosine Kinases/genetics , Protein-Tyrosine Kinases/metabolism , RNA, Small Interfering/genetics , Saccharomyces cerevisiae Proteins/genetics , Urea/pharmacology
15.
Cell Rep ; 5(6): 1714-24, 2013 Dec 26.
Article in English | MEDLINE | ID: mdl-24360959

ABSTRACT

Efficient repair of UV-induced DNA damage requires the precise coordination of nucleotide excision repair (NER) with numerous other biological processes. To map this crosstalk, we generated a differential genetic interaction map centered on quantitative growth measurements of >45,000 double mutants before and after different doses of UV radiation. Integration of genetic data with physical interaction networks identified a global map of 89 UV-induced functional interactions among 62 protein complexes, including a number of links between the RSC complex and several NER factors. We show that RSC is recruited to both silenced and transcribed loci following UV damage where it facilitates efficient repair by promoting nucleosome remodeling. Finally, a comparison of the response to high versus low levels of UV shows that the degree of genetic rewiring correlates with dose of UV and reveals a network of dose-specific interactions. This study makes available a large resource of UV-induced interactions, and it illustrates a methodology for identifying dose-dependent interactions based on quantitative shifts in genetic networks.


Subject(s)
Chromatin Assembly and Disassembly , DNA Repair , Gene Regulatory Networks/radiation effects , Saccharomyces cerevisiae/genetics , Ultraviolet Rays , Dose-Response Relationship, Radiation , Genome, Fungal , Saccharomyces cerevisiae/metabolism , Saccharomyces cerevisiae/radiation effects , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism
16.
Cell Rep ; 3(1): 128-37, 2013 Jan 31.
Article in English | MEDLINE | ID: mdl-23291096

ABSTRACT

Classic "position-effect" experiments repositioned genes near telomeres to demonstrate that the epigenetic landscape can dramatically alter gene expression. Here, we show that systematic gene knockout collections provide an exceptional resource for interrogating position effects, not only near telomeres but at every genetic locus. Because a single reporter gene replaces each deleted gene, interrogating this reporter provides a sensitive probe into different chromatin environments while controlling for genetic context. Using this approach, we find that, whereas systematic replacement of yeast genes with the kanMX marker does not perturb the chromatin landscape, chromatin differences associated with gene position account for 35% of kanMX activity. We observe distinct chromatin influences, including a Set2/Rpd3-mediated antagonistic interaction between histone H3 lysine 36 trimethylation and the Rap1 transcriptional activation site in kanMX. This interaction explains why some yeast genes have been resistant to deletion and allows successful generation of these deletion strains through the use of a modified transformation procedure. These findings demonstrate that chromatin regulation is not governed by a uniform "histone code" but by specific interactions between chromatin and genetic factors.


Subject(s)
Chromosomal Position Effects/genetics , Epigenesis, Genetic , Gene Order/genetics , Saccharomyces cerevisiae/genetics , Acetylation , Chromatin/metabolism , Chromosomes, Fungal/genetics , Diploidy , Gene Deletion , Gene Expression Regulation, Fungal , Gene Knockout Techniques , Gene Library , Genes, Fungal/genetics , Genetic Markers , Heterozygote , Histones/metabolism , Lysine/metabolism , Methylation , Mutagenesis, Insertional/genetics , Promoter Regions, Genetic/genetics , Protein Binding/genetics , Protein Processing, Post-Translational/genetics , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism , Signal Transduction/genetics
17.
Science ; 330(6009): 1385-9, 2010 Dec 03.
Article in English | MEDLINE | ID: mdl-21127252

ABSTRACT

Although cellular behaviors are dynamic, the networks that govern these behaviors have been mapped primarily as static snapshots. Using an approach called differential epistasis mapping, we have discovered widespread changes in genetic interaction among yeast kinases, phosphatases, and transcription factors as the cell responds to DNA damage. Differential interactions uncover many gene functions that go undetected in static conditions. They are very effective at identifying DNA repair pathways, highlighting new damage-dependent roles for the Slt2 kinase, Pph3 phosphatase, and histone variant Htz1. The data also reveal that protein complexes are generally stable in response to perturbation, but the functional relations between these complexes are substantially reorganized. Differential networks chart a new type of genetic landscape that is invaluable for mapping cellular responses to stimuli.


Subject(s)
DNA Damage , DNA Repair/genetics , Epistasis, Genetic , Gene Regulatory Networks , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae/metabolism , Chromatin/metabolism , DNA, Fungal/genetics , Genes, Fungal , Histones/genetics , Histones/metabolism , Methyl Methanesulfonate/pharmacology , Mitogen-Activated Protein Kinases/genetics , Mitogen-Activated Protein Kinases/metabolism , Mutagens/pharmacology , Mutation , Phosphoprotein Phosphatases/genetics , Phosphoprotein Phosphatases/metabolism , Protein Interaction Mapping , Protein Serine-Threonine Kinases/genetics , Protein Serine-Threonine Kinases/metabolism , Saccharomyces cerevisiae Proteins/genetics , Signal Transduction , Transcription Factors/genetics , Transcription Factors/metabolism
18.
Genome Res ; 20(12): 1672-8, 2010 Dec.
Article in English | MEDLINE | ID: mdl-20978140

ABSTRACT

Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of "coevolution" between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.


Subject(s)
Candida glabrata/genetics , Evolution, Molecular , Gene Regulatory Networks/genetics , Mutation/genetics , Transcription Factor AP-1/genetics , Amino Acid Sequence , Base Sequence , Chromatin Immunoprecipitation , Microarray Analysis/methods , Molecular Sequence Data , Sequence Analysis, DNA , Transcription Factor AP-1/metabolism
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